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        "<table class=\"ee-notebook-buttons\" align=\"left\">\n",
        "    <td><a target=\"_blank\"  href=\"https://github.com/giswqs/earthengine-py-notebooks/tree/master/JavaScripts/Demos/TerrainVisualization.ipynb\"><img width=32px src=\"https://www.tensorflow.org/images/GitHub-Mark-32px.png\" /> View source on GitHub</a></td>\n",
        "    <td><a target=\"_blank\"  href=\"https://nbviewer.jupyter.org/github/giswqs/earthengine-py-notebooks/blob/master/JavaScripts/Demos/TerrainVisualization.ipynb\"><img width=26px src=\"https://upload.wikimedia.org/wikipedia/commons/thumb/3/38/Jupyter_logo.svg/883px-Jupyter_logo.svg.png\" />Notebook Viewer</a></td>\n",
        "    <td><a target=\"_blank\"  href=\"https://colab.research.google.com/github/giswqs/earthengine-py-notebooks/blob/master/JavaScripts/Demos/TerrainVisualization.ipynb\"><img src=\"https://www.tensorflow.org/images/colab_logo_32px.png\" /> Run in Google Colab</a></td>\n",
        "</table>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Install Earth Engine API and geemap\n",
        "Install the [Earth Engine Python API](https://developers.google.com/earth-engine/python_install) and [geemap](https://github.com/giswqs/geemap). The **geemap** Python package is built upon the [ipyleaflet](https://github.com/jupyter-widgets/ipyleaflet) and [folium](https://github.com/python-visualization/folium) packages and implements several methods for interacting with Earth Engine data layers, such as `Map.addLayer()`, `Map.setCenter()`, and `Map.centerObject()`.\n",
        "The following script checks if the geemap package has been installed. If not, it will install geemap, which automatically installs its [dependencies](https://github.com/giswqs/geemap#dependencies), including earthengine-api, folium, and ipyleaflet.\n",
        "\n",
        "**Important note**: A key difference between folium and ipyleaflet is that ipyleaflet is built upon ipywidgets and allows bidirectional communication between the front-end and the backend enabling the use of the map to capture user input, while folium is meant for displaying static data only ([source](https://blog.jupyter.org/interactive-gis-in-jupyter-with-ipyleaflet-52f9657fa7a)). Note that [Google Colab](https://colab.research.google.com/) currently does not support ipyleaflet ([source](https://github.com/googlecolab/colabtools/issues/60#issuecomment-596225619)). Therefore, if you are using geemap with Google Colab, you should use [`import geemap.eefolium`](https://github.com/giswqs/geemap/blob/master/geemap/eefolium.py). If you are using geemap with [binder](https://mybinder.org/) or a local Jupyter notebook server, you can use [`import geemap`](https://github.com/giswqs/geemap/blob/master/geemap/geemap.py), which provides more functionalities for capturing user input (e.g., mouse-clicking and moving)."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {},
      "source": [
        "# Installs geemap package\n",
        "import subprocess\n",
        "\n",
        "try:\n",
        "    import geemap\n",
        "except ImportError:\n",
        "    print('geemap package not installed. Installing ...')\n",
        "    subprocess.check_call([\"python\", '-m', 'pip', 'install', 'geemap'])\n",
        "\n",
        "# Checks whether this notebook is running on Google Colab\n",
        "try:\n",
        "    import google.colab\n",
        "    import geemap.eefolium as geemap\n",
        "except:\n",
        "    import geemap\n",
        "\n",
        "# Authenticates and initializes Earth Engine\n",
        "import ee\n",
        "\n",
        "try:\n",
        "    ee.Initialize()\n",
        "except Exception as e:\n",
        "    ee.Authenticate()\n",
        "    ee.Initialize()  "
      ],
      "outputs": [],
      "execution_count": null
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Create an interactive map \n",
        "The default basemap is `Google MapS`. [Additional basemaps](https://github.com/giswqs/geemap/blob/master/geemap/basemaps.py) can be added using the `Map.add_basemap()` function. "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {},
      "source": [
        "Map = geemap.Map(center=[40,-100], zoom=4)\n",
        "Map"
      ],
      "outputs": [],
      "execution_count": null
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Add Earth Engine Python script "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {},
      "source": [
        "# Add Earth Engine dataset\n",
        "# Use an elevation dataset and terrain functions to create\n",
        "# a custom visualization of topography.\n",
        "\n",
        "# Load a global elevation image.\n",
        "elev = ee.Image('USGS/GMTED2010')\n",
        "\n",
        "# Zoom to an area of interest.\n",
        "Map.setCenter(-121.069, 50.709, 6)\n",
        "\n",
        "# Add the elevation to the map.\n",
        "Map.addLayer(elev, {}, 'elev')\n",
        "\n",
        "# Use the terrain algorithms to compute a hillshade with 8-bit values.\n",
        "shade = ee.Terrain.hillshade(elev)\n",
        "Map.addLayer(shade, {}, 'hillshade', False)\n",
        "\n",
        "# Create a \"sea\" variable to be used for cartographic purposes\n",
        "sea = elev.lte(0)\n",
        "Map.addLayer(sea.mask(sea), {'palette':'000022'}, 'sea', False)\n",
        "\n",
        "# Create a custom elevation palette from hex strings.\n",
        "elevationPalette = ['006600', '002200', 'fff700', 'ab7634', 'c4d0ff', 'ffffff']\n",
        "# Use these visualization parameters, customized by location.\n",
        "visParams = {'min': 1, 'max': 3000, 'palette': elevationPalette}\n",
        "\n",
        "# Create a mosaic of the sea and the elevation data\n",
        "visualized = ee.ImageCollection([\n",
        "  # Mask the elevation to get only land\n",
        "  elev.mask(sea.Not()).visualize(visParams),\n",
        "  # Use the sea mask directly to display sea.\n",
        "  sea.mask(sea).visualize(**{'palette':'000022'})\n",
        "]).mosaic()\n",
        "\n",
        "# Note that the visualization image doesn't require visualization parameters.\n",
        "Map.addLayer(visualized, {}, 'elev palette', False)\n",
        "\n",
        "# Convert the visualized elevation to HSV, first converting to [0, 1] data.\n",
        "hsv = visualized.divide(255).rgbToHsv()\n",
        "# Select only the hue and saturation bands.\n",
        "hs = hsv.select(0, 1)\n",
        "# Convert the hillshade to [0, 1] data, as expected by the HSV algorithm.\n",
        "v = shade.divide(255)\n",
        "# Create a visualization image by converting back to RGB from HSV.\n",
        "# Note the cast to byte in order to export the image correctly.\n",
        "rgb = hs.addBands(v).hsvToRgb().multiply(255).byte()\n",
        "Map.addLayer(rgb, {}, 'styled')\n",
        "\n"
      ],
      "outputs": [],
      "execution_count": null
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Display Earth Engine data layers "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {},
      "source": [
        "Map.addLayerControl() # This line is not needed for ipyleaflet-based Map.\n",
        "Map"
      ],
      "outputs": [],
      "execution_count": null
    }
  ],
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